fabric-spark-compute-perf-remediatelisted

# Fabric Delta Lake & Spark Performance remediate Systematic remediate toolkit for diagnosing and resolving performance issues across Microsoft Fabric Spark compute, Delta Lake tables, and Lakehouse workloads. ## When to Use This Skill - Spark notebooks or jobs running slower than expected - Delta table queries degrading over time (small file problem) - Capacity throttling errors (HTTP 430 / TooManyRequestsForCapacity) - Session startup taking minutes instead of seconds - Out-of-memory errors on executors or drivers - Streaming ingestion falling behind or producing small files - VOrder or resource profile misconfiguration - Deciding between read-heavy vs. write-heavy workload profiles - Planning table maintenance (OPTIMIZE, VACUUM, Z-Order) - Tuning autoscaling, dynamic executor allocation, or autotune ## Prerequisites - Access to a Microsoft Fabric workspace with Data Engineering enabled - Contributor or higher role on the workspace - Fabric capacity (F2+) or Trial capacity - PowerShell 7+ for diagnostic scripts - PySpark for notebook-based diagnostics ## Triage: Identify the Symptom Category Start by matching the observed symptom to one of these categories, then follow the linked reference for the detailed workflow. | Symptom | Category | Reference | | ---------------------------------------- | --------------------- | -------------------------------------------------------